Abstract:

The distinctive characteristics of the agricultural milieu, current economic conditions and the many dramatic changes that impacted on the sector the last decade are only a few problems which the commercial farmer has to face. These problems do not only impact on the agricultural producer, but also on the secondary and tertiary sectors which link directly and indirectly to the agricultural sector. Therefore all the systematic and unsystematic risk factors do not only have an effect on the agricultural producer, but also on the commercial bank as a provider of finance. The basic issue with respect to risk-bearing ability is whether or not the farm operation can withstand financial losses without being forced into liquidation or insolvency. Financial risks are influenced by other business risks, such as production risk, price risk, health risk, risk of obsolescence, and innovation. If production and prices decline, resulting in reduced profits or even losses, these losses must be covered or absorbed out of equity capital or net worth. Financial risks are also influenced by the proportion of debt and equity included in the farm business. Thus, with higher leverage or higher debt in relation to equity or total assets, losses can be magnified and financial risk becomes much greater. The main objective of the thesis flows from the above problem statement, namely to identify variables which can serve as indicators for financial viability (risk bearing ability) and to use the identified variables to predict financial viability (distinguish between producers who had failed versus those who were financially successful) in a quantitative manner. The various existing techniques for the prediction of business failure which have been examined all indicated that financial viability depends on the following factors: (1) The solvency of the farm operation. (2) The magnitude and structure of loan capital. (3) The ability of the manager to employ capital both effective and efficiently. This will ensure that sufficient income and profits will always be generated to meet all capital and interest payments. The most successful approach to financial failure prediction is multiple discriminant and regression analysis. Both techniques were used to analyse a set of 26 independent variables for statistical significance in the projection of financial success versus failure. A total of six independent variables were computer-selected as significant in the projection of financial success/failure over the medium term. The functions were derived at by using historical data of a sample of farm operations that either failed (50) or succeeded (50) financially during the past two years. Both the multiple discriminant functions and the multiple linear regression functions were highly successful in distinguishing between producers who had failed financially versus those who were financially successful. The following conclusions were made out of the survey: (1) The causes of agribusiness failure are numerous, and they vary from situation to situation. However the major underlying causes are financial factors which include too much debt, insufficient capital together with inadequate risk-bearing ability and repayment capacity. (2) The results reveal a need for an overall improvement in financial and risk management. (3) Existing techniques to predict financial success/failure are difficult to apply in practice due to the fact that the values of the independent variables are not freely available. Some of the existing models have not been tested on the agricultural sector as such. The functions which were fitted in this study overcame these problems and can easily be applied in the commercial bank environment to determine the risk bearing ability of its clients. (4) The models which were developed succeeded to a large extend in the prediction of financial success and failure. (5) The results have important practical implications for both the commercial farmers as well as the commercial bank.